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Steel Special Welding Non-destructive Testing And Flaw Signal Recognition System Design And Implementation

Posted on:2011-11-19Degree:MasterType:Thesis
Country:ChinaCandidate:H B WangFull Text:PDF
GTID:2208330332477220Subject:Software engineering
Abstract/Summary:PDF Full Text Request
This project aims at improving the detection skill of construction steel-structure of Zhejiang Institute of Building Research and Design and making an effort to realize non-destructive detection digitally. Traditional ultrasonic flaw detector works under analog circuit which is composed of discrete components. Such equipment can only fulfill basic functions such as acceptance of echo, amplification of signal and displaying, operation is complicated and analysis and flaw detection on echo mainly depend on detectors and their practical experience. Thus, measurement accuracy is comparative low and subjective errors are more. The latest ultrasonic flaw detection technique (digital completely) which combines ultrasonic phased array and TOFD imaging system becomes a new trend. This research includes software for non-destructive detection and location of steel-structure; identification system of flaw signals and relative supporting database and hardware.This paper mainly focuses on research and development of non-destructive detection of construction steel structure. It makes use of powerful computing capability and rich software and hardware of computer to realize functions of location, identification, displaying, channel controlling, storage and printing. It greatly improves efficiency of equipment cost, also improve its intelligence. Accordingly, manual detection of flaws is more convenient and flexible. Research on modern digital signal processing and flaw detection mode of non-destructive weld detection not only improves accuracy of detection, but also makes detection results such as size, location and property of weld flaws quantitatively.
Keywords/Search Tags:Pattern Recognition of Weld Defects, Ultrasonic testing video review, Ultrasonic flaw detection of static and dynamic image
PDF Full Text Request
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